Most enterprises store their massive volumes of transactional and analytics data at rest in data warehouses or data lakes. Sales, marketing, and customer success teams require access to these data sets. Reverse ETL is a buzzword that defines the concept of collecting data from existing data stores to provide it easy and quick for business teams.
This blog post explores why software vendors (try to) introduce new solutions for Reverse ETL, when it is needed, and how it fits into the enterprise architecture. The involvement of event streaming with tools like Apache Kafka to process data in motion is a crucial piece of Reverse ETL for real-time use cases.